By Mr Md Shariful Alam

Journal articles

Alam MS; Wang D; Arzhaeva Y; Ende JA; Kao J; Silverstone L; Yates D; Salvado O; Sowmya A, 2024, 'Attention-based multi-residual network for lung segmentation in diseased lungs with custom data augmentation', Scientific Reports, 14, http://dx.doi.org/10.1038/s41598-024-79494-w

Alam MS; Wang D; Sowmya A, 2024, 'DLA-Net: dual lesion attention network for classification of pneumoconiosis using chest X-ray images', Scientific Reports, 14, http://dx.doi.org/10.1038/s41598-024-61024-3

Alam MS; Wang D; Sowmya A, 2024, 'AMFP-net: Adaptive multi-scale feature pyramid network for diagnosis of pneumoconiosis from chest X-ray images', Artificial Intelligence in Medicine, 154, http://dx.doi.org/10.1016/j.artmed.2024.102917

Alam MS; Wang D; Liao Q; Sowmya A, 2023, 'A Multi-Scale Context Aware Attention Model for Medical Image Segmentation', IEEE Journal of Biomedical and Health Informatics, 27, pp. 3731 - 3739, http://dx.doi.org/10.1109/JBHI.2022.3227540

Rahman SM; Alam MS; Zubair A; Shahriar MH; Hossein M; Alam MS; Hefler M, 2019, 'Graphic health warnings on tobacco packets and containers: compliance status in Bangladesh.', Tob Control, 28, pp. 261 - 267, http://dx.doi.org/10.1136/tobaccocontrol-2018-054249

Ahmad MM; Rahman SM; Alam MS, 2016, 'From strategy to execution: the case of local climate fund in Bangladesh', International Journal of Environmental Policy and Decision Making, 2, pp. 1 - 1, http://dx.doi.org/10.1504/ijepdm.2016.10001372

Conference Papers

Alam MS; Wang D; Sowmya A, 2021, 'Bidirectional Convolutional-LSTM based Network for lung segmentation of chest X-ray images', in Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI, pp. 915 - 919, http://dx.doi.org/10.1109/ICTAI52525.2021.00147

Alam MS; Wang D; Sowmya A, 2021, 'Image data augmentation for improving performance of deep learning-based model in pathological lung segmentation', in DICTA 2021 - 2021 International Conference on Digital Image Computing: Techniques and Applications, http://dx.doi.org/10.1109/DICTA52665.2021.9647209

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